Anesthesiology

Artificial intelligence chatbots versus traditional medical resources for patient education on "Labor Epidurals": an evaluation of accuracy, emotional tone, and readability.

BACKGROUND: Labor epidural analgesia is a widely used method for pain relief in childbirth, yet information accessibility for expectant mothers remains a challenge. Artificial intelligence (AI) chatbots like Chat Generative Pre-Trained Transformer (ChatGPT) and Google Gemini offer potential solutions for improving patient education. This study evaluates the accuracy, readability, and emotional ton...

Predicting Epidural Hematoma Expansion in Traumatic Brain Injury: A Machine Learning Approach.

IntroductionTraumatic brain injury (TBI) is a leading cause of disability and mortality worldwide, with epidural hematoma (EDH) being a severe consequence. This study focuses on identifying factors predicting EDH volume changes in TBI patients and developing a machine learning (ML) model to predict EDH expansion.MethodsThe study includes patients with traumatic EDH between 2019 and 2021. Data were...

Comprehensive prediction of outcomes in patients with ST elevation myocardial infarction (STEMI) using tree-based machine learning algorithms.

ST elevation myocardial infarction (STEMI), a subtype of acute coronary syndrome, is one of the leading causes of morbidity and mortality. Revasculari...

Perioperative risk scores: prediction, pitfalls, and progress.

PURPOSE OF REVIEW: Perioperative risk scores aim to risk-stratify patients to guide their evaluation and management. Several scores are established in...

Explainable predictions of a machine learning model to forecast the postoperative length of stay for severe patients: machine learning model development and evaluation.

BACKGROUND: Predicting the length of stay in advance will not only benefit the hospitals both clinically and financially but enable healthcare provide...

Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and this issue has yet to be conclusively resolved. The...

Artificial intelligence-based drug repurposing with electronic health record clinical corroboration: A case for ketamine as a potential treatment for amphetamine-type stimulant use disorder.

BACKGROUND AND AIMS: Amphetamine-type stimulants are the second-most used illicit drugs globally, yet there are no US Food and Drug Administration (FD...

Artificial intelligence-created personal statements compared with applicant-written personal statements: a survey of obstetric anesthesia fellowship program directors in the United States.

BACKGROUND: A personal statement is a common requirement in medical residency and fellowship applications. Generative artificial intelligence may be u...

Glottic opening detection using deep learning for neonatal intubation with video laryngoscopy.

OBJECTIVE: This study aimed to develop an artificial intelligence (AI) method to augment video laryngoscopy (VL) by automating the detection of the gl...

Development and external validation of an interpretable machine learning model for the prediction of intubation in the intensive care unit.

Given the limited capacity to accurately determine the necessity for intubation in intensive care unit settings, this study aimed to develop and exter...

Combining Fiber Bragg Grating and Artificial Intelligence Technologies for Supporting Epidural Procedures.

OBJECTIVE: Loss of resistance (LOR) is a widely accepted method for performing epidural punctures in clinical settings. However, the risk of failure a...

Artificial intelligence in obstetric anaesthesiology - the future of patient care?

The use of artificial intelligence (AI) in obstetric anaesthesiology shows great potential in enhancing our practice and delivery of care. In this nar...

Automatic Segmentation of Ultrasound-Guided Quadratus Lumborum Blocks Based on Artificial Intelligence.

Ultrasound-guided quadratus lumborum block (QLB) technology has become a widely used perioperative analgesia method during abdominal and pelvic surger...

Machine learning-augmented interventions in perioperative care: a systematic review and meta-analysis.

BACKGROUND: We lack evidence on the cumulative effectiveness of machine learning (ML)-driven interventions in perioperative settings. Therefore, we co...

Effect of ethanol extract of nigella sativa L seeds and propofol on BDNF protein level as neuroplasticity and neuroprotection of traumatic brain injury in rats.

BACKGROUND: Traumatic brain injury (TBI) is a change in brain function or evidence of brain pathology caused by external mechanical forces. Brain Deri...

Machine learning-based prediction of the risk of moderate-to-severe catheter-related bladder discomfort in general anaesthesia patients: a prospective cohort study.

BACKGROUND: Catheter-related bladder discomfort (CRBD) commonly occurs in patients who have indwelling urinary catheters while under general anesthesi...

Effect of a novel artificial intelligence-based cecum recognition system on adenoma detection metrics in a screening colonoscopy setting.

BACKGROUND AND AIMS: Cecal intubation in colonoscopy relies on self-reporting. We developed an artificial intelligence-based cecum recognition system ...

Accurate Machine Learning-based Monitoring of Anesthesia Depth with EEG Recording.

General anesthesia, pivotal for surgical procedures, requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to post...

Unsupervised Machine Learning to Identify Risk Factors of Pyeloplasty Failure in Ureteropelvic Junction Obstruction.

In adult patients with ureteropelvic junction obstruction (UPJO), little data exist on predicting pyeloplasty outcome, and there is no unified defini...

Predicting stroke volume variation using central venous pressure waveform: a deep learning approach.

. This study evaluated the predictive performance of a deep learning approach to predict stroke volume variation (SVV) from central venous pressure (C...